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Title: QUANTIFICATION OF FATTY ACIDS IN FORAGES BY NEAR-INFRARED REFLECTANCE SPECTROSCOPY

Author
item Foster, Joyce
item Clapham, William
item Fedders, James

Submitted to: Journal of Agricultural and Food Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/6/2006
Publication Date: 4/1/2006
Citation: Foster, J.G., Clapham, W.M., Fedders, J.M. 2006. Quantification of Fatty Acids in Forages by Near-Infrared Reflectance Spectroscopy. Journal of Agricultural and Food Chemistry. 54:3186-3192.

Interpretive Summary: Fatty acids in ruminant diets influence the fatty acid composition of meat and milk derived from the animals. Forage fatty acids that serve as precursors of beneficial omega-3 fatty acids and conjugated linoleic acid in meat and milk vary with plant species and stage of growth, the environment to which plants are exposed, and the management strategies that are imposed. Knowledge of the fatty acid composition of pasture species can help producers market animals with defined characteristics. Existing analytical procedures for forage fatty acid determination are time-consuming and require hazardous chemicals, expensive equipment, and skilled technical personnel. Near infrared reflectance spectroscopy (NIRS) is a rapid, nondestructive procedure that is routinely used in forage testing laboratories. This study was undertaken to determine whether NIRS can be used for quantification of forage fatty acids. Results indicate that NIRS will give good estimates for forage fatty acids. Determination of fatty acid composition of dry herbage using NIRS could be easily incorporated into forage testing protocols with minimal increase in analytical cost. With appropriate calibration equations, a single spectral scan can be used to determine traditional forage quality indicators such as crude protein, fiber content, and digestibility, as well as fatty acid composition.

Technical Abstract: Near infrared reflectance spectroscopy (NIRS) was evaluated as a possible alternative to gas chromatographic (GC) procedures for quantitative analysis of fatty acids in forage. Herbage samples from 13 greenhouse-grown grasses, legumes, and forbs were collected at three stages of growth. Samples were freeze-dried, ground and analyzed by GC and NIRS techniques. One-half of the 195 samples were used to develop an NIRS calibration file for each of seven fatty acids, with the remaining half used as a validation data set. Spectral data, collected over a wavelength range of 1100 to 2498 nm, were regressed against GC data to develop calibration equations for lauric, myristic, palmitic, stearic, oleic, linoleic, and '-linolenic acids. Calibration equations had high coefficients of determination for calibration (R2 = 0.93 to 0.99) and cross validation [1-variance ratio (1-VR) = 0.89 to 0.98], and low standard error of calibration (SEC) and low standard error of cross validation (SECV) (SEC and SECV < 20% of the mean). Simple linear regressions of NIRS results against GC data for the validation data set had R2 values ranging from 0.88 to 0.97. Regression slopes for lauric, myristic, palmitic, stearic, linoleic, and '-linolenic acids were not significantly different (P = 0.05) from 1.0. The regression slope for oleic acid was 1.1. Results indicate that NIRS has high prediction ability for fatty acids in forages. Calibration equations developed using data for all plant materials accurately predicted concentrations of palmitic, linoleic, and '-linolenic acids in individual plant species. Accuracy of prediction was less for fatty acids (lauric, myristic, stearic, and oleic) that were less prevalent.